Structuring element

About: Structuring element is a research topic. Over the lifetime, 997 publications have been published within this topic receiving 26839 citations.

Comparison of filters dedicated to speckle suppression in sar images

Abstract: This paper presents the results of research on the effectiveness of different filtering methods dedicated to speckle suppression in SAR images. The tests were performed on RadarSat-2 images and on an artificial image treated with simulated speckle noise. The research analysed the performance of particular filters related to the effectiveness of speckle suppression and to the ability to preserve image details and edges. Speckle is a phenomenon inherent to radar images – a deterministic noise connected with land cover type, but also causing significant changes in digital numbers of pixels. As a result, it may affect interpretation, classification and other processes concerning radar images. Speckle, resembling “salt and pepper” noise, has the form of a set of relatively small groups of pixels of values markedly different from values of other pixels representing the same type of land cover. Suppression of this noise may also cause suppression of small image details, therefore the ability to preserve the important parts of an image, was analysed as well. In the present study, selected filters were tested, and methods dedicated particularly to speckle noise suppression: Frost, Gamma-MAP, Lee, Lee-Sigma, Local Region, general filtering methods which might be effective in this respect: Mean, Median, in addition to morphological filters (alternate sequential filters with multiple structuring element and by reconstruction). The analysis presented in this paper compared the effectiveness of different filtering methods. It proved that some of the dedicated radar filters are efficient tools for speckle suppression, but also demonstrated a significant efficiency of the morphological approach, especially its ability to preserve image details.

A fast implementation of 1-D grayscale morphological filters

Abstract: This paper presents an algorithm for the fast implementation of 1-D grayscale morphological filters with set structuring elements. The algorithm is developed by filter property analysis, instead of by architecture design. It performs an opening or closing with a single pass procedure. The average number of operations required is less than three comparisons per sample for openings and closings, which is independent of the size of the structuring element used. >

Spatially-Variant Directional Mathematical Morphology Operators Based on a Diffused Average Squared Gradient Field

Abstract: This paper proposes an approach for mathematical morphology operators whose structuring element can locally adapt its orientation across the pixels of the image. The orientation at each pixel is extracted by means of a diffusion process of the average squared gradient field. The resulting vector field, the average squared gradient vector flow, extends the orientation information from the edges of the objects to the homogeneous areas of the image. The provided orientation field is then used to perform a spatially variant filtering with a linear structuring element. Results of erosion, dilation, opening and closing spatially-variant on binary images prove the validity of this theoretical sound and novel approach.

A background based adaptive page segmentation algorithm

Abstract: A novel page segmentation algorithm is provided in this paper. Based on the extraction of the background, it offers the benefit of being adaptive to the context of the document and to be insensitive to the orientation of the text blocks. It involves a two-dimensional isotropic structuring element used to characterized the white streams. This element is a disk approximated by a regular octagon which can be recursively generated. Another advantage of the proposed method is that a hierarchical segmentation can be derived from the image built upon the octagonal pattern. This tree allows to perform an isotropic multi-scale smearing, which leads to a physical segmentation. The algorithms are based on an input-time tracing principle and use a single scan of the image, they are very well suited to a real-time implementation.